Results 91 to 100 of about 74,563 (305)
FEBS Letters, EarlyView.An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
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FEBS Letters, EarlyView.Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
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Hierarchical kernel spectral clustering [PDF]
Neural Networks, 2012 Kernel spectral clustering fits in a constrained optimization framework where the primal problem is expressed in terms of high-dimensional feature maps and the dual problem is expressed in terms of kernel evaluations. An eigenvalue problem is solved at the training stage and projections onto the eigenvectors constitute the clustering model.
Alzate Perez, Carlos, Suykens, Johan
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Sensors, 2022 Hyperspectral imaging can simultaneously acquire spectral and spatial information of the samples and is, therefore, widely applied in the non-destructive detection of grain quality.
Zhen Kang +5 more
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Molecular Oncology, EarlyView.Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
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Covariate-assisted spectral clustering [PDF]
Biometrika, 2017 28 pages, 4 figures, includes substantial changes to theoretical ...
Norbert Binkiewicz +2 more
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An Improvement of Spectral Clustering via Message Passing and Density Sensitive Similarity
IEEE Access, 2019 Spectral clustering transforms the data clustering problem into a graph-partitioning problem and classifies data points by finding the optimal sub-graphs. Traditional spectral clustering algorithms use Gaussian kernel function to construct the similarity
Lijuan Wang, Shifei Ding, Hongjie Jia
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PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining.
Y. Z. Gu +5 more
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Molecular Oncology, EarlyView.In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera +11 more
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Scientific Reports, 2017 A major challenge in clinical cancer research is the identification of accurate molecular subtype. While unsupervised clustering methods have been applied for class discovery, this clustering method remains a bottleneck in developing accurate method for ...
Mingguang Shi, Guofu Xu
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